1. This is a real picture, the physical camel is a white line on the desert floor
And hey, these camels might even be clustered!.

2. Lower 48
14064

4. California and Georgia

8. Is there a background. How many clusters are there
Is there a background? How many clusters are there? Do they have a characteristic size? Is there substructure? Are there any peculiar boundary conditions?

9. Nice approach

10. Now starting to see voids here

11. Circles are Better

13. Is most of your volume filled with Cluster or Voids
Define some void density = some under density; count in circular sizes and see how many circles of what size meet your defined threshold

15. There does seem to be a typical value
The long tail is the background – in the case where there are about as many events in the background as in the clusters, the nearest neighbor statistics will be about 1 (random) but will become much smaller if you subtract the background out.
In this case there are more points in the clusters than in the background
Average = 6.7 KM

16. Sliding Boxes –this approach tends to truncate the long tail
Average = 8.5 km – now you have learned something

23. Use this approach – in K-means all points are part of some cluster
High central over density compared to background